The present invention relates to a signal conversion processing apparatus and, more particularly to a signal conversion processing apparatus for temporarily storing an analog signal such as an image signal representing the luminance of each pixel of an image and processing the signal to generate a desired output signal.
An image signal obtained from an image sensing element such as a CCD is an analog signal formed by discretely plotting the luminance of pixels of an image on the time axis. Each luminance is represented by an analog value as the amplitude of the analog signal.
As the analog value, not only a value continuously changing but also a multilevel value changing stepwise is used.
To reconstruct image signals of the primary RGB colors (red, green, and blue) from an image signal obtained from an image sensing element having a color filter, the RGB luminance must be calculated for all omitted pixels by pixel interpolation.
For such signal processing, a signal conversion processing apparatus for temporarily storing an analog signal and processing the signal to generate a desired output signal is used.
To perform pixel interpolation of this type in a conventional digital camera system, an image signal obtained from an image sensing element is converted into a digital value by an A/D converter, and then, interpolation calculation is performed by program processing using an MPU or DSP.
On the other hand, in a full-analog camera system such as a video camera system, real-time pixel interpolation is performed for image signals of the respective colors basically using only addition and subtraction, and the signals are directly output to a display apparatus.
Image enlargement/reduction, distortion correction, spatial filter processing, and noise reduction are also included in image data processing. These processing operations can be regarded as interpolation for determining a new pixel (luminance) value.
In this case, for interpolation calculation, not only linear interpolation but also various methods such as a cubic convolution or B spline method using interpolation expressions of higher order can be used.
As convolution calculation for changing the image size, a separation scheme of calculation a one-dimensional convolution kernel in each of the vertical (Y) and horizontal (X) directions of an image or a scheme using direct action of a two-dimensional convolution kernel can be used.
In conversion of the luminance value of each pixel by white balance processing or gamma correction processing, once the value is quantized by A/D conversion, the density resolution is insufficient, and high-quality correction cannot be performed. Hence, in a conventional digital electronic camera system, after an image signal is converted into a digital value by a highly accurate A/D converter, the luminance value of each pixel is converted using predetermined conversion characteristics.
In such a conventional signal conversion processing apparatus, however, after an input analog signal is quantized by an A/D converter, arithmetic processing is performed using an MPU or a DSP to execute desired conversion processing. For this reason, if a processor with a considerably high processing speed is used, a large load is generated to lower the throughput of the entire signal conversion processing.
For example, when the above-described RGB pixel interpolation is performed for an image signal comprised of about 1,000,000 pixels, a calculation time of several sec to several ten sec is required even with a simple algorithm, i.e., linear interpolation from four nearest points.
Use of a higher-order interpolation algorithm increases the information processing amount in progression.
The clock rate of an MPU or DSP is limited. If the clock rate can be increased, memory circuits connected must also allow access at a higher speed, resulting in a large increase in cost.
To increase the processing capability, a plurality of MPUs or DSPs as interpolation calculators may be simultaneously operated, though this method poses problems of manufacturing cost, power consumption, and mounting space.
As the spatial resolution is improved by increasing the number of pixels, to increase the density resolution using the conventional digital processing method, the accuracy of quantization must be increased by increasing the number of conversion bits of an A/D converter. This increases the data processing load on all circuits in proportion to the conversion bit width.
In the above-described full-analog system, it is difficult to hold data for a long time to perform all pixel interpolation operations as analog processing. For example, data of about one line of an output from the image sensing element is held and delayed, and only a limited number of data of the next line are used for calculation. Hence, the range and method of interpolation are considerably limited.